While exploring the world and the associated conservation issues I've been noting down my reflections and discoveries. Some posts are more organized while others are simple notes.

I generally focus on conservation issues effecting biodiversity, land use/abuse, research, and job opportunities that I have come across. Most of the opportunities come from the Opps page and you can click on the button below to take you there.

Surrogate ideaThis idea was thrown around casually in reference to using “the next best thing” as a substitute for an unknown characteristic in a system’s equation. This is a cool idea because it allows you to proceed with an idea even if you don’t know all the components. It allows you to work on and estimate interactions while being honest about lacking full knowledge. I wrote the term down and then tried to look it up and found subpar definitions. The best I found was in reference to electrical engineering and developing circuitry even if not everything is present:“A surrogate model is an engineering method used when an outcome of interest cannot be easily directly measured, so a model of the outcome is used instead. Most engineering design problems require experiments and/or simulations to evaluate design objective and constraint functions as function of design variables. For example, in order to find the optimal airfoil shape for an aircraft wing, an engineer simulates the air flow around the wing for different shape variables (length, curvature, material, ..).”With a little more digging I found how it relates to Critical Theory. Below are two hyperlinks that play with the idea.https://www.psychologicalscience.org/publications/observer/2009/february-09/surrogates-for-theory.htmlhttps://www.mpib-berlin.mpg.de/volltexte/institut/dok/full/gg/GG_Surr_1998.pdfI think this could be helpful in SocioEcological Systems Theory and a surrogate of a critical unknown could be used to help solve a wicked problem.Thinking too hardI was busy doing busy work this week and didn’t learn too much new. However, I did have the idea that I am too concerned with knowing all the constituent parts that I don’t allow myself to learn what’s going on. In effect, I am getting in my own way, making things more difficult than they need to be and that is stopping me from learning. I believe our weaknesses are our strengths in excess and my strength is in understanding the narrative. My weakness though may just be in hamstringing myself until I learn the whole thing before being able to comprehend the parts. This is playing out in Statistics. I think I am making it more difficult than it needs to be.

​System vs Piece Thinking

I’m trying to understand ecological ideas and social studies together and these present themselves as systems. I’ve looked at Chaos systems, Socio-Ecological Systems, and Complex Systems but I never thought about what a system is or how to define it. Specifically, there is a way of thinking different from normal ‘Piece’ Thinking called ‘Systems Thinking’. I’m trying to understand it but Wikipedia has a pretty comprehensive explanation of it:

Systems thinking has been defined as an approach to problem solving that attempts to balance holistic thinking and reductionistic thinking. By taking the overall system as well as its parts into account systems thinking is designed to avoid potentially contributing to further development of unintended consequences. There are many methods and approaches to systems thinking. For example, the Waters Foundation presents systems thinking as a set of habits or practices within a framework that is based on the belief that the component parts of a system can best be understood in the context of relationships with each other and with other systems, rather than in isolation; and that systems thinking focuses on cyclical rather than linear cause and effect. Other models characterize systems thinking differently. Recent scholars, however, are focused on the "patterns that connect" this diversity or pluralism of methods and approaches.

Several ways to think of and define a system include:

a system is composed of parts

a system is greater than the sum of its parts

all the parts of a system must be related (directly or indirectly), else there are really two or more distinct systems

a system is encapsulated (has a boundary)

a system can be nested inside another system

a system can overlap with another system

a system is bounded in time, but may be intermittently operational

a system is bounded in space, though the parts are not necessarily co-located

a system receives input from, and sends output into, the wider environment

a system consists of processes that transform inputs into outputs

a system is autonomous in fulfilling its purpose (a car is not a system. A car with a driver is a system)

Systems science thinkers consider that:

A system is a dynamic and complex whole, interacting as a structured functional unit circuit.

Energy, material and information flow among the different elements that compose a system (see open system).

A system is a community within an environment.

Energy, material, and information flow from and to the surrounding environment via semi-permeable membranes or boundaries that may include negotiable limits.

Hard systems – involving simulations, hard systems approaches to system thinking often use computers and the techniques of operations research/management science. Hard systems approaches are useful for problems that can be justifiably quantified. However, hard systems cannot easily account for unquantifiable variables such as opinions, culture, or politics, etc.,[citation needed] and may treat people as passive elements, rather than as beings with complex motivations.

Soft systems (or soft systems methodology) – is a methodology for systems that cannot easily be quantified, especially systems that involve people holding multiple and conflicting frames of reference. Soft systems methods are useful for understanding motivations, viewpoints, and interactions, and for addressing qualitative as well as quantitative dimensions of problem situations. Soft systems approaches to system thinking may use foundation methodological work developed by Peter Checkland, Brian Wilson, and their colleagues at Lancaster University. This approach may include morphological analysis, which is a complementary method for structuring and analyzing non-quantifiable problem complexes.

Evolutionary systems – Béla H. Bánáthy developed a methodology that is applicable to the design of complex social systems. This technique integrates critical systems inquiry with soft systems methodologies. Evolutionary systems, similar to dynamic systems are understood as open, complex systems, but with the capacity to evolve over time. Bánáthy uniquely integrated the interdisciplinary perspectives of systems research (including chaos, complexity, cybernetics), cultural anthropology, evolutionary theory, and others.